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概要と使いどころ
Build DSPy evaluation harnesses with rich-feedback metrics that are essential for GEPA optimization. Use when writing a metric function, calling dspy.Evaluate, splitting dev/val sets, debugging "why is my optimizer not improving?", or designing CI-ready DSPy eval suites.
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Optimize DSPy programs with dspy.GEPA — a reflective/evolutionary optimizer to consider against task-specific baselines within an authorized evaluation budget. Use when the user says optimize, compile, GEPA, reflective optimization, or "make this program better" and a DSPy program + metric + trainset exist.
日本語の概要は準備中です。原文の説明を表示しています。
Builds a complete Google Ads keyword strategy with search intent mapping, ad group structure, match type recommendations, negative keyword lists, estimated CPC ranges, Quality Score optimization, and ready-to-implement campaign architecture
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Landing Page Audit & Optimizer. Analyzes landing pages for ad-to-page alignment, message match, CTA clarity, trust signals, mobile optimization, and form friction. Generates specific rewrite suggestions with before/after copy, or builds a complete landing page outline from scratch.
日本語の概要は準備中です。原文の説明を表示しています。
Optimize slow PostgreSQL inserts in Python using psycopg2. Use when: (1) Row-by-row inserts are taking too long over network, (2) executemany() isn't providing speedup, (3) Migrating large datasets to PostgreSQL, (4) Network latency making individual INSERT statements impractical. The key is using execute_values() from psycopg2.extras instead of executemany() or individual execute() calls.
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Write SEO pages that rank on Google AND get cited by LLMs. Uses live SERP data, 500-token chunk architecture, RAG optimization for Gemini 3.5 Flash, the Two-Gate AEO framework (retrieval-pool entry + selected-citation extraction), the Anti-NLP Stuffing Protocol (structural entity placement, no keyword-density stuffing), strict single-service local isolation, and the Reddit Test quality gate. Triggers on: "write an SEO page", "seo-agi", "seo page for [keyword]", "rank for [keyword]", "rewrite this page for SEO", "GEO", "AEO", "write a page that ranks".
日本語の概要は準備中です。原文の説明を表示しています。
Forecast inventory needs using demand analysis, safety stock calculations, reorder point optimization, and seasonal adjustment
日本語の概要は準備中です。原文の説明を表示しています。
Analyze and improve business processes. Trigger with "this process is slow", "how can we improve", "streamline this workflow", "too many steps", "bottleneck", or when the user describes an inefficient process they want to fix.
日本語の概要は準備中です。原文の説明を表示しています。
Automatically simplify and minimize TLA+ specifications by reducing redundant state variables, merging equivalent actions, and minimizing invariants while preserving specified properties. Use when working with TLA+ specifications that need optimization, simplification, or reduction. Triggers when users ask to minimize, reduce, simplify, or optimize TLA+ specs, or when they want to remove redundancy from formal specifications while maintaining semantic equivalence.
日本語の概要は準備中です。原文の説明を表示しています。
Hardware verification tool for checking functional equivalence between two RTL designs (Verilog). Use when users need to: (1) Verify if two RTL versions are functionally equivalent, (2) Compare original vs. refactored RTL code, (3) Validate design changes or optimizations, (4) Identify semantic vs. cosmetic differences, (5) Generate counterexamples for non-equivalent designs. Analyzes interface alignment, state variables, logic differences, and produces detailed equivalence verdicts with plain language explanations. Particularly effective for design verification, code reviews, and regression testing of RTL modifications.
日本語の概要は準備中です。原文の説明を表示しています。
Profile programs at the function/method level to identify performance hotspots, bottlenecks, and optimization opportunities. Records execution time, memory usage, and call frequency for each interval. Generates actionable recommendations and visualizations. Use when users need to (1) analyze program performance, (2) identify slow functions or bottlenecks, (3) optimize execution time or memory usage, (4) profile Python, Java, or C/C++ programs with test cases or workload scenarios, or (5) generate performance reports with flame graphs and recommendations.
日本語の概要は準備中です。原文の説明を表示しています。
When the user wants to optimize, improve, or increase conversions on any marketing page or form — including homepage, landing pages, pricing pages, feature pages, lead capture forms, or contact forms. Also use when the user says 'CRO,' 'conversion rate optimization,' 'this page isn't...
日本語の概要は準備中です。原文の説明を表示しています。
Audit Meta Ads measurement, Pixel and Conversions API, attribution, Facebook and Instagram creative, audiences, placements, automation, budgets, account structure, and policy. Use for Meta Ads, Facebook Ads, Instagram Ads, Advantage+, Pixel, CAPI, Events Manager, creative fatigue, or Meta campaign optimization.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user wants a research-paper figure Skill Factory: build, patch, package, or use reusable specialized paper-figure-making skills from lawful literature/corpus evidence. Generated skills must use a specialized-skill-first workflow, full-feasible local PDF coverage where available, startup-plan-only first replies, target-paper candidate/final image isolation, mandatory image-embedded visual-structure explanation, mandatory non-target concept/modeling example display for abstract visual decisions, saved subtype/style illustration atlases, ChatGPT web Create image / ChatGPT Images 2.0 rendering, Codex $imagegen-first rendering, sample-image transfer rules, all-step/current-position state footers, and a mandatory first-round diverse candidate board followed by P6b/P6c paper-local best-practice optimization before final prompt construction.
日本語の概要は準備中です。原文の説明を表示しています。
Half-Quadratic Quantization for LLMs without calibration data. Use when quantizing models to 4/3/2-bit precision without needing calibration datasets, for fast quantization workflows, or when deploying with vLLM or HuggingFace Transformers.
日本語の概要は準備中です。原文の説明を表示しています。
Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.
日本語の概要は準備中です。原文の説明を表示しています。
Audit component performance and identify optimization opportunities with actionable fixes
日本語の概要は準備中です。原文の説明を表示しています。
Optimize content for AI search engines — ChatGPT, Perplexity, Claude, Gemini, Google AI Overviews. Use when the user asks about AI SEO, AISO, getting cited by AI, appearing in AI answers, answer engine optimization, AEO, GEO, LLMO, AI Overviews, zero-click search, or how to appear in ChatGPT/Perplexity results. For traditional SEO, see diagnose-seo.
日本語の概要は準備中です。原文の説明を表示しています。
When the user wants to audit, review, or diagnose SEO issues on their site. Also use when the user mentions "SEO audit," "technical SEO," "why am I not ranking," "SEO issues," "on-page SEO," "meta tags review," "SEO health check," "my traffic dropped," "lost rankings," "not showing up in Google," "site isn't ranking," "Google update hit me," "page speed," "core web vitals," "crawl errors," or "indexing issues." Use this even if the user just says something vague like "my SEO is bad" or "help with SEO" — start with an audit. For building pages at scale to target keywords, see programmatic-seo. For adding structured data, see schema. For AI search optimization, see ai-seo.
日本語の概要は準備中です。原文の説明を表示しています。
| Turborepo monorepo build system guidance. Triggers on: turbo.json, task pipelines, dependsOn, caching, remote cache, the "turbo" CLI, --filter, --affected, CI optimization, environment variables, internal packages, monorepo structure/best practices, and boundaries. Use when user: configures tasks/workflows/pipelines, creates packages, sets up monorepo, shares code between apps, runs changed/affected packages, debugs cache, or has apps/packages directories.
日本語の概要は準備中です。原文の説明を表示しています。
SEO optimization with keyword analysis, readability assessment, technical validation, content quality. Use for search rankings, blog posts, content audits, or encountering keyword density, readability scores, meta tags, schema markup errors.
日本語の概要は準備中です。原文の説明を表示しています。
Optimizes web application performance through code splitting, lazy loading, caching strategies, and Core Web Vitals monitoring. Use when improving page load times, implementing service workers, or reducing bundle sizes.
日本語の概要は準備中です。原文の説明を表示しています。
| Nuxt 5 production optimization: hydration, performance, testing with Vitest, deployment to Cloudflare/Vercel/Netlify, and migration from Nuxt 4. Use when: debugging hydration mismatches, optimizing performance and Core Web Vitals, writing tests with Vitest, deploying to Cloudflare Pages/Workers/Vercel/Netlify, or migrating from Nuxt 4 to Nuxt 5.
日本語の概要は準備中です。原文の説明を表示しています。
| Nuxt 4 production optimization: hydration, performance, testing with Vitest, deployment to Cloudflare/Vercel/Netlify, and v4 migration. Use when: debugging hydration mismatches, optimizing performance and Core Web Vitals, writing tests with Vitest, deploying to Cloudflare Pages/Workers/Vercel/Netlify, or migrating from Nuxt 3 to Nuxt 4.
日本語の概要は準備中です。原文の説明を表示しています。